ArticleAmerican health & drug benefits2021
Effects of the Medicare Part D Comprehensive Medication Review on Racial and Ethnic Disparities in Medication Adherence.
Article in American health & drug benefits, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 2 citations in OpenAlex.
- Racial and ethnic disparities in Medicare Part D medication therapy management services utilization.Exploratory research in clinical and social pharmacy · 2023Article
- Effects of the Medicare Part D Comprehensive Medication Review on Racial and Ethnic Disparities in Medication Adherence.American health & drug benefits · 2021Article
- Disparity implications of machine-learning-based MTM eligibility criteria.Journal of the American Pharmacists Association : JAPhAArticle
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Background: Substantial research has documented inequalities between US minorities and whites in meeting the eligibility criteria for the Medicare Part D medication therapy management (MTM) program. Even though the Centers for Medicare & Medicaid Services attempted to relax the eligibility criteria, a critical barrier to effective MTM reform is a lack of stronger evidence about the effects of MTM on minorities' health outcomes. Objective: To examine the effects of comprehensive medication review (CMR), an MTM core component, on racial and ethnic disparities in adherence to diabetes, hypertension, and hyperlipidemia medications among Medicare beneficiaries aged ≥65 years. Methods: This study used full-year 2017 Medicare Parts A, B, and D claims data, including MTM data, linked to the Area Health Resources Files. Racial and ethnic disparities in nonadherence to diabetes, hypertension, and hyperlipidemia medications were compared between CMR recipients and nonrecipients matched by their propensity scores. To determine the changes in racial and ethnic disparities after receiving CMR, a difference-in-differences framework was applied, by including in logistic regression analyses interaction terms between dummy variables for CMR receipt and each racial or ethnic minority group. Results: Compared with CMR nonrecipients, CMR recipients had significantly lower racial and ethnic disparities across the 3 outcome measures, with the exception of the difference between whites and blacks in nonadherence to diabetes medications. For example, compared with CMR nonrecipients, among CMR recipients the differences in the odds of nonadherence to hypertension medications were reduced, respectively, by 8% (95% confidence interval [CI], 0.88-0.96) between whites and blacks; by 18% (95% CI, 0.78-0.86) between whites and Hispanics; by 16% (95% CI, 0.77-0.91) between whites and Asians; and by 9% (95% CI, 0.85-0.98) between whites and other racial and ethnic groups. Conclusion: Receiving a CMR reduced the racial and ethnic disparities in adherence to diabetes, hypertension, and hyperlipidemia medications among Medicare beneficiaries aged ≥65 years. These findings provide critical empirical evidence that may inform the future design of the Medicare Part D MTM program, which is valuable for improving pharmacotherapy outcomes and could further realize its potential when additional people from racial and ethnic minorities are enrolled.
Indexed as
Identifiers
35261713PMC8845523W4287007185What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.